Sustainable Real-Time 8K60 HEVC Encoding for V2X: Repurposing Legacy NVENC Hardware at the Vehicular Edge

2026-05-15

AI Summary

This work addresses the challenges of low-latency, low-power edge encoding for 8K60 video in vehicle-road collaboration and teleoperation scenarios, where hardware costs, supply chain constraints, and e-waste concerns limit deployment. The authors innovatively repurpose legacy NVIDIA Pascal GPUs (GP104/GP102) by leveraging their NVENC hardware units and propose a dual-NVENC parallel frame-split encoding strategy. This approach achieves ultra-low-latency real-time HEVC encoding on Pascal’s B-frame-free architecture. Notably, the study reveals—for the first time—that smaller GPU dies exhibit superior energy efficiency over flagship models in fixed-function encoding tasks. The system incurs less than 1% rate-distortion loss at 8K60, significantly reducing power consumption and electronic waste, thereby offering a cost-effective and environmentally sustainable edge video encoding solution for intelligent transportation systems.

Abstract

The rapid advancement of Vehicle-to-Everything (V2X) communications and Tele-Operated Driving (ToD) demands ultra-low-latency, 8K60 video telemetry. However, deploying modern hardware at the vehicular edge is frequently hindered by supply chain constraints, high power budgets, and growing e-waste concerns. This paper investigates a highly sustainable alternative: repurposing legacy NVIDIA Pascal GPUs for real-time 8K HEVC edge encoding. We demonstrate that triggering 2-Way Split Frame Encoding (SFE) on dual-NVENC GP104 and GP102 silicon successfully unlocks real-time 8K60 throughput with a negligible Rate-Distortion penalty of under 1%. Crucially, our micro-architectural analysis reveals that smaller GPU dies significantly outperform larger flagship models in both raw throughput and energy efficiency. Because fixed-function encoding forces general-purpose Streaming Multiprocessor (SM) cores to sustain maximum frequencies while remaining idle, GPUs with fewer CUDA cores waste drastically less power. While benchmarking against the state-of-the-art RTX PRO 6000 Blackwell highlights a generational compression efficiency gap, Pascal's functional HEVC architecture and native lack of B-frames align perfectly with ultra-low-latency V2X pipelines. Ultimately, repurposed mid-range Pascal GPUs present a highly capable, cost-effective, and e-waste mitigating solution for modern Intelligent Transportation Systems.

Problem

• V2X
• 8K60 video encoding
• sustainable computing
• edge encoding
• e-waste mitigation

Innovation

• Split Frame Encoding
• Legacy GPU Repurposing
• NVENC
• Ultra-Low-Latency HEVC
• Energy-Efficient Edge Encoding